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COVID-Bot, an Intelligent System for COVID-19 Vaccination Screening: Design and Development

Overview
Journal JMIR Form Res
Publisher JMIR Publications
Date 2022 Oct 27
PMID 36301616
Authors
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Abstract

Background: Coronavirus continues to spread worldwide, causing various health and economic disruptions. One of the most important approaches to controlling the spread of this disease is to use an artificial intelligence (AI)-based technological intervention, such as a chatbot system. Chatbots can aid in the fight against the spread of COVID-19.

Objective: This paper introduces COVID-Bot, an intelligent interactive system that can help screen students and confirm their COVID-19 vaccination status.

Methods: The design and development of COVID-Bot followed the principles of the design science research (DSR) process, which is a research method for creating a new scientific artifact. COVID-Bot was developed and implemented using the SnatchBot chatbot application programming interface (API) and its predefined tools, which are driven by various natural language processing algorithms.

Results: An evaluation was carried out through a survey that involved 106 university students in determining the functionality, compatibility, reliability, and usability of COVID-Bot. The findings indicated that 92 (86.8%) of the participants agreed that the chatbot functions well, 85 (80.2%) agreed that it fits well with their mobile devices and their lifestyle, 86 (81.1%) agreed that it has the potential to produce accurate and consistent responses, and 85 (80.2%) agreed that it is easy to use. The average obtained α was .87, indicating satisfactory reliability.

Conclusions: This study demonstrates that incorporating chatbot technology into the educational system can combat the spread of COVID-19 among university students. The intelligent system does this by interacting with students to determine their vaccination status.

Citing Articles

Overview of Chatbots with special emphasis on artificial intelligence-enabled ChatGPT in medical science.

Chakraborty C, Pal S, Bhattacharya M, Dash S, Lee S Front Artif Intell. 2023; 6:1237704.

PMID: 38028668 PMC: 10644239. DOI: 10.3389/frai.2023.1237704.


Voice-Based Screening for SARS-CoV-2 Exposure in Cardiovascular Clinics (VOICE-COVID-19-II): Protocol for a Randomized Controlled Trial.

Oulousian E, Chung S, Ganni E, Razaghizad A, Zhang G, Avram R JMIR Res Protoc. 2023; 12:e41209.

PMID: 36719720 PMC: 9891354. DOI: 10.2196/41209.

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